5 Essential Elements of AI Governance

What is AI Governance?

According to IBM, Artificial Intelligence (AI) Governance refers to the “processes, standards, and guardrails that help ensure AI systems and tools are safe and ethical”. AI Governance is becoming increasingly important due to the rise of daily AI use for businesses. The Globalization Partners second-annual AI at Work Report revealed that:

• 91% of global executives are actively scaling up AI initiatives.
• 74% of executives use AI for more than 25% of their work.
• 82 % of HR leaders believe AI is essential to their company’s success.

By aligning your AI use with these 5 essential elements of AI governance, you can manage risk, ensure ethical use, and align AI with business and compliance standards tailored to your industry.

1. Acceptable Use Guidelines

A strong AI Governance framework begins with defining what “acceptable” AI use means for business. This includes establishing clear boundaries for employee use of AI tools, ensuring a shared understanding of what’s safe across the organization.

Without these acceptable use guidelines, employees are at risk of unknowingly exposing sensitive information or introducing regulatory risk. This can happen when staff, often with good intentions, input confidential data into public AI platforms that may store or repurpose that information.

In some cases, this can result in breaches of client confidentiality, violations of industry-specific compliance rules, or the unintentional distribution of inaccurate or unverified AI-generated content under your company’s name.

• Public AI tools like ChatGPT, Microsoft CoPilot, or Claud may store, reuse, or share data, which can create legal and security concerns.
• Clearly define which tools are approved for use, and provide safe alternatives for common tasks employees might normally complete with unapproved AI tools like ChatGPT.
• Where possible, adopt enterprise-secure versions of popular AI tools (e.g., Microsoft Copilot for Microsoft 365, ChatGPT Enterprise, Google Gemini for Workspace, Claude Enterprise) that offer enhanced security, compliance alignment, and admin oversight. Including these in your acceptable use policy helps employees understand not just what’s prohibited, but also which AI options are safe, approved, and supported by the organization.
• Provide accessible resources, like our AI Acceptable Use Cheat Sheet, to make guidelines easy to reference and remember.

2. Risk & Security Management

Effective AI governance must include how AI tools affect your data privacy, cybersecurity protections, compliance requirements, and ownership of your work. A growing concern is that employees may unknowingly put sensitive information—like customer records, financial reports, or internal project plans—into public AI tools. Once entered, that data may be stored on external servers, reused to train the AI, or even become accessible to people outside your organization. This creates serious risks around:

• Cybersecurity: Hackers could target AI platforms to steal stored information.
• Compliance: Sharing sensitive information, such as patient data (healthcare) or client account details (finance), could break laws and result in fines.
• Intellectual Property: Your unique ideas, designs, or strategies could be reused by the AI or show up in outputs given to other users.

This step ensures that your AI use meets the same safety, security, and compliance standards as your business’s other technologies and data.

• AI can contribute to shadow IT, unapproved tools that bypass security controls.
• Some AI vendors retain data for training, which can violate compliance rules like HIPAA, GDPR, or GLBA.
• Conducting a security risk assessment before approving AI tools can prevent costly breaches and fines. Pair this with a documented incident response plan so your team knows exactly how to respond if AI-related data loss, misuse, or compliance violations occur.

In IBM’s 2025 Cost of a Data Breach report, 20% of organizations experienced a breach due to “shadow AI”, unauthorized AI tools, with these breaches costing an additional $670,000 on average. Only 3% of those affected had proper AI access controls in place.

3. Oversight & Accountability

Strong AI governance begins with well-defined ownership and accountability. Someone in your business, often a cross-functional team, should be responsible for approving AI tools, maintaining policies, and ensuring safe adoption. Centralizing oversight prevents fragmented or unsafe use across departments and ensures AI is evaluated from both a technical and operational standpoint.

• Cross-functional oversight should include IT, HR, Legal, and Operations to address both the technical and operational risks of AI use in the workplace.
• An AI tool might meet all your cybersecurity requirements but still create problems elsewhere, like slowing down workflows, conflicting with existing processes, or introducing compliance gaps. A dedicated oversight team can evaluate new tools for both security and real-world business impact before adoption.
• Partnering with a trusted IT provider can strengthen AI governance by integrating it into your broader technology and security strategy.

4. Employee Education & Awareness

Ongoing education for staff to understand AI risks and how to use tools safely. Policies are only effective if employees understand them. A knowledgeable workforce is your strongest defense.

• Nearly 60% of data breaches in 2024 involved a human element, such as mistakes or manipulation, demonstrating that even smart tools can’t compensate for a lack of awareness
• Provide accessible quick reference materials, such as our AI Acceptable Use cheat sheet or department-specific dos and don’ts.
• Include AI safety training and refresher sessions to keep up with evolving AI governance practices.
• Foster a culture of open communication where employees can ask questions related to AI without fear.

According to KnowBe4’s 2025 Phishing by Industry Benchmarking Report, organizations that implemented security awareness training saw phishing susceptibility drop by 40% within 90 days—and by up to 86% after a year.

5. Monitoring

As of 2025, 71% of companies report using generative AI in at least one business function, up from 65% in early 2024. This rapid growth shows just how quickly AI tools for business are evolving, and as AI changes, so must your governance. A proactive and flexible strategy helps keep your organization secure, compliant, and aligned with both technological advancements and regulatory updates. Staying informed and adaptable protects not just your data, but also your employees and your overall business operations.

• Set a policy review cadence to remain up to date on emerging AI capabilities and threats. Read our article on The Keys to Proactive Cybersecurity.
• Collect feedback from employees and managers to identify real-world policy gaps.
• Track usage patterns to ensure AI tools are being used appropriately and retire those that no longer meet your needs or standards.

Responsible AI Starts with Understanding

AI governance isn’t just about compliance, it’s about building the guardrails that let your business innovate and scale confidently. From setting clear acceptable use guidelines to monitoring adoption over time, these five elements work together to protect sensitive data, reduce risk, and ensure AI tools are used ethically and effectively across your organization.

The right approach to governance will look different for every business, but the goal is the same: enable your teams to leverage AI’s benefits without exposing your company to unnecessary risk. By staying informed, fostering awareness, and evolving your policies as AI advances, you create a culture where safe, responsible AI use becomes second nature.

Ready to take the next step?

Explore our library of free AI governance and education resources to help you share best practices, set expectations, and empower employees to use AI safely:

⬇️ AI Acceptable Use Cheat Sheet 

⬇️ AI Use Policy Checklist (for internal governance teams)